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Discrete Region Competition for Unknown Numbers of Connected Regions

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3 Author(s)
Cardinale, J. ; MOSAIC Group, ETH Zurich, Zurich, Switzerland ; Paul, G. ; Sbalzarini, I.F.

We present a discrete unsupervised multiregion-competition algorithm for image segmentation over different energy functionals. The number of regions present in an image does not need to be known a priori, nor their photometric properties. The algorithm jointly estimates the number of regions, their photometries, and their contours. The required regularization is provided by defining a region as a connected set of pixels. The evolving contours in the image are represented by computational particles that move as driven by an energy-minimization algorithm. We present an efficient discrete algorithm that allows minimizing a range of well-known energy functionals under the topological constraint of regions being connected components. The presented framework and algorithms are implemented in the open-source Insight Toolkit image-processing library.

Published in:

Image Processing, IEEE Transactions on  (Volume:21 ,  Issue: 8 )